Mobile networking method and system for minimizing interference

ABSTRACT

The invention provides a mobile networking method and system for minimizing interference. The mobile networking method comprises the following steps: unmanned aerial vehicles establish connection and communication with ground base stations through a wireless relay method; connection and communication between the unmanned aerial vehicles are established through a wireless self-networking method; multiple unmanned aerial vehicles cooperate to form a cellular network to provide wireless network services for users; the unmanned aerial vehicles receive a received signal strength indicator fed back by user equipment and measure the angle of arrival of a signal beam from the user equipment; the main lobe of a signal is made to aim at the direction of arrival of service users and the null is made to aim at the direction of arrival of interference signals through a mobile interference alignment method and a beam forming method, and thus the optimal hovering position is searched out. The invention has the following beneficial effects: interference between adjacent cells is reduced through the mobility of the unmanned aerial vehicle sub-base stations, and existing wireless network equipment is mainly adopted and no professional equipment is needed, so that the method and system have extremely high universality.

BACKGROUND Technical Field

The invention relates to the technical field of wireless communications,and particularly relates to a mobile networking method and system forminimizing interference.

Description of Related Art

With the continuous development of the wireless communication technique,more and more wireless network devices are used, and accordingly, thenumber of wireless access points is increased. In 3G and 4G, the cellcoverage becomes smaller, the number of base stations is increased, andconsequentially, the cell edges become blurred; and meanwhile, severeinter-cell interference is inevitably caused by high frequency spectrummultiplexing coefficients. Wireless network service providers devote tocreating an approach which can reduce interference while ensuringeffective service area coverage so as to provide high-qualitycommunication services. According to existing networking methods, basestations in a cell are generally located at fixed positions,interference is worsened while the number of users in the cell isincreased, and consequentially, the user communication quality in thecell is reduced.

Traditional networking methods all have the problem of severeinterference under high user density conditions, and base stations areimmobile.

SUMMARY OF THE INVENTION

The invention provides a mobile networking method for minimizinginterference. The mobile networking method for minimizing interferencecomprises the following steps:

S1, unmanned aerial vehicles establish connection and communication withground base stations through a wireless relay method;

S2, connection and communication between the unmanned aerial vehiclesare established through a wireless self-networking method;

S3, multiple unmanned aerial vehicles cooperate to form a cellularnetwork to provide wireless network services for users;

S4, the unmanned aerial vehicles receive a received signal strengthindicator fed back by user equipment and measure the angle of arrival ofa signal beam from the user equipment;

S5, the unmanned aerial vehicles share the measurement informationobtained in step S4, a cellular network signal for service users of aspecific unmanned aerial vehicle is regarded as a desired signal,cellular network signals of other unmanned aerial vehicles are regardedas interference signals, the main lobe of the desired signal is made toaim at the direction of arrival of the service users and the null ismade to aim at the direction of arrival of the interference signalsthrough a mobile interference alignment method and a beam formingmethod, and thus the optimal hovering position is searched out;

S6, when the position of the user equipment changes, step S4 and step S5are repeated to search out the optimal hovering position again.

As a further improvement of the invention, in step S1, the unmannedaerial vehicles establish connection and communication with the groundbase stations through the wireless relay method, and the link frequencyis different from the communication frequency between the sub-basestations and users.

As a further improvement of the invention, in step S3, multiple unmannedaerial vehicles cooperate, flight of the unmanned aerial vehicles isdetermined through a distributed control method, each unmanned aerialvehicle covers a certain area and provides wireless network services forusers in the area, and all the unmanned aerial vehicles form the mobilecellular network.

As a further improvement of the invention, step S4 comprises:

S41, the user equipment monitors the signal intensities of the unmannedaerial vehicles and feeds the information back to the unmanned aerialvehicles;

S42, the unmanned aerial vehicles receive signals from the serviceusers, and the direction of arrival of the user equipment is estimatedthrough the MUSIC algorithm.

As a further improvement of the invention, step S5 comprises:

S51, the unmanned aerial vehicles share the information obtained in stepS4 through the self network;

S52, based on the mobile interference alignment method, each unmannedaerial vehicle searches out a position where interference from thecellular network signals of other unmanned aerial vehicles is minimizedthrough a random hill climbing algorithm;

S53, the main lobe of the signal of each unmanned aerial vehicle is madeto aim at the corresponding service users through the beam formingtechnique, and thus interference to other user equipment is reduced;

S54, the optimal hovering position is searched out based on step S52 andstep S53.

The invention further provides a mobile networking system for minimizinginterference. The mobile networking system for minimizing interferencecomprises:

a signal acquisition module, wherein unmanned aerial vehicles areequipped with multiple antennas and acquire signals from user equipmentas well as channel state information;

a signal analysis module, wherein the signal analysis module is used fordetermining the direction of arrival of the user equipment through theMUSIC algorithm;

a signal processing module, wherein the signal processing moduleachieves beam forming through precoding according to known signal stateinformation;

a position searching module, wherein the position searching module isused for assisting each unmanned aerial vehicle in searching out ahovering position where interference to other unmanned aerial vehiclesis small through a random hill climbing algorithm.

As a further improvement of the invention, the signal acquisition modulecomprises:

an acquisition module, wherein noise and out-of-band interferencesignals are filtered out through a band-pass filter for wireless signalsacquired by the unmanned aerial vehicles according to the operatingfrequency of the equipment, so that to-be-processed signals areobtained, and the channel state information of the physical layer isalso obtained.

As a further improvement of the invention, the signal analysis modulecomprises:

a main path information extraction unit, wherein multi-path componentsarriving at a receiving antenna along different paths are separated bymeans of chromatic dispersion of a multi-path signal in the time domainand the power delay distribution characteristic, a power threshold valueis set, the path signal, greater than the power threshold, of the usersignal is regarded as main path information, and the main pathinformation is transformed from the time domain to the frequency domainthrough fast Fourier transform;

an angle of arrival calculation unit, wherein according to phasedeviation of the signal arriving at an antenna array, the timedifference of arrival of the signal at different antennas can be workedout, and the angle of arrival θ of the user signal along the direct pathis worked out through the MUSIC algorithm according to the differenttimes of arrival of the signal at the antenna array.

As a further improvement of the invention, the signal processing modulecomprises:

a CSI processing unit, wherein the CSI processing unit is used forsmoothing acquired CSI data so as to eliminate signal coherence;

a beam forming unit, wherein based on the smoothed CSI data, a formingmatrix is calculated, the main lobe of the signal aims at the directionof arrival of the user signal, and the null aims at the direction ofarrival of interference signals, so that the radiant power of thesub-base stations is reduced, and interference to other users is alsoreduced.

As a further improvement of the invention, the position searching modulecomprises:

a field distribution calculation unit, wherein for adjacent unmannedaerial vehicles, spatial distribution of wireless signals is estimatedaccording to known position information and a standard propagation modelof the wireless signals in the space;

a position searching unit, wherein through the random hill climbingalgorithm, each unmanned aerial vehicle searches out a position wherethe signal intensity of the adjacent unmanned aerial vehicle is weak andthen hovers at the position.

The invention has the following beneficial effects: interference betweenadjacent cells is reduced through the mobility of the unmanned aerialvehicle sub-base stations, and existing wireless network equipment aremainly adopted and no professional equipment is needed, so that themobile networking method for minimizing interference has extremely highuniversality.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an implementation flow diagram of a mobile networking methodof the invention;

FIG. 2 is a location diagram for the mobile networking method of theinvention; and

FIG. 3 is a framework diagram of a mobile networking system of theinvention.

DESCRIPTION OF THE EMBODIMENTS

The invention discloses a mobile networking method for minimizinginterference. The mobile networking method for minimizing interferencecomprises the following steps:

S1, unmanned aerial vehicles establish connection and communication withground base stations through a wireless relay method;

S2, connection and communication between the unmanned aerial vehiclesare established through a wireless self-networking method;

S3, multiple unmanned aerial vehicles cooperate to form a cellularnetwork to provide wireless network services for users;

S4, the unmanned aerial vehicles receive a received signal strengthindicator (RSSI) fed back by user equipment and measure the angle ofarrival (AoA) of a signal beam from the user equipment;

S5, the unmanned aerial vehicles share the measurement informationobtained in step S4, a cellular network signal for service users of aspecific unmanned aerial vehicle is regarded as a desired signal,cellular network signals of other unmanned aerial vehicles are regardedas interference signals, the main lobe of the desired signal is made toaim at the direction of arrival of the service users and the null ismade to aim at the direction of arrival of the interference signalsthrough a mobile interference alignment method and a beam formingmethod, and thus the optimal hovering position is searched out;

S6, when the position of the user equipment changes, step S4 and step S5are repeated to search out the optimal hovering position again.

In actual application, multi-antenna transceivers are used for receivingwireless signals, and the sub-base stations are umnanned aerialvehicles. According to the fact that a specific umnanned aerial vehiclehas different degrees of interference to other umnanned aerial vehicleswhen located at different positions, the mobile networking method isbased on the mobility of the unmanned aerial vehicle, and interferenceto other users is reduced through the beam forming method. Severeinterference can be generated between base stations operating at thesame frequency, and interference of the same frequency cannot befiltered out by band-pass filters. To obtain the direction of arrival ofthe service users, the direct path component of a user signal need to beseparated out, and the angle of arrival of the beam is obtained throughthe MUSIC algorithm. Through moving and beam forming, interferencebetween the sub-base stations and interference to the users from thesub-base stations can be minimized.

Specifically, in step S1, the unmanned aerial vehicles serve as aerialsub-base stations and establish connection and communication with theground base stations through the wireless relay method, and meanwhile,for avoiding new interference, the link frequency is different from thecommunication frequency between the sub-base stations and the users.

When the system starts to operate, the unmanned aerial vehicle locatedon the network edge is connected to the nearest ground base station, andthe frequency points of the uplink and the downlink are different fromthe frequency points of the cellular network.

In step S2, the sub-base stations are self-networked so as to beconnected and communicated.

In step S3, multiple unmanned aerial vehicles cooperate, and flight ofthe unmanned aerial vehicles is determined through a distributed controlmethod. Each unmanned aerial vehicle covers a certain area and provideswireless network services for users in the area. All the unmanned aerialvehicles form the mobile cellular network.

In the outdoor environment, due to the existence of reflectors such asbuildings and trees, signals reach the receiving terminal from thetransmitting terminal along many paths, and the times of arrival and theangles of arrival of the signals transmitted along different paths aredifferent. The degrees of attenuation of the signals transmitted alongdifferent paths are also different, and chromatic dispersion of thesignals can be caused in the time domain. The signals transmitted alongshort paths reach the antenna array earlier, the signals transmittedalong long paths reach the antenna array late, and thus the direct pathcomponent can be separated from non-direct path components through powerdelay distribution. A power threshold is preset, and the signal greaterthan the power threshold is regarded as the possible direct pathcomponent. The signal with short delay is regarded as the direct pathcomponent and is transformed to the frequency domain from the timedomain through FFT so as to be input in the next step.

In step S4, the process of calculating the angle of arrival of usersignals comprises:

S41, the user equipment monitors the signal intensities of the unmannedaerial vehicles and feeds the information back to the unmanned aerialvehicles;

S42, the unmanned aerial vehicles receive the signals from the serviceusers, and the direction of arrival of the user equipment is estimatedthrough the MUSIC algorithm.

In step S5, the process of searching for the minimum interferenceposition comprises:

S51, the unmanned aerial vehicles share the information obtained in stepS4 through the self network;

S52, based on the mobile interference alignment method, each unmannedaerial vehicle searches out a position where interference from thecellular network signals of other unmanned aerial vehicles is minimizedthrough a random hill climbing algorithm;

S53, the main lobe of the signal of each unmanned aerial vehicle is madeto aim at the corresponding service users through the beam formingtechnique, and thus interference to other user equipment is reduced;

S54, the optimal hovering position is searched out based on step S52 andstep S53.

Specifically, as is shown in FIG. 1, the process of locating an indoorinterference source comprises the steps:

1) the unmanned aerial vehicles are connected to the ground basestations at a frequency point different from that of a terminal network;

2) the unmanned aerial vehicles are connected and communicated throughthe self-networking method;

3) a mobile cellular network formed by multiple unmanned aerial vehiclesprovides services for users;

4) user terminal equipment monitors the received signal intensity of thesub-base stations;

5) the sub-base stations acquire signals from user terminals;

6) the angle of arrival of the signals from the user terminals isobtained through the MUSIC algorithm;

7) the main lobe of the signal from the base stations is made to aim atthe users through the beam forming technique according to the angle ofarrival, and thus interference to users in other directions is reduced;

8) the unmanned aerial vehicles move and search out the positions whereinterference to adjacent base stations is small according to thepositions of the unmanned aerial vehicles.

The invention further discloses a mobile networking system forminimizing interference. The mobile networking system for minimizinginterference comprises:

a signal acquisition module, wherein unmanned aerial vehicles areequipped with multiple antennas and acquire signals from user equipmentas well as channel state information;

a signal analysis module, wherein the signal analysis module is used fordetermining the direction of arrival of the user equipment through theMUSIC algorithm;

a signal processing module, wherein the signal processing moduleachieves beam forming through precoding according to known signal stateinformation;

a position searching module, wherein the position searching module isused for assisting each unmanned aerial vehicle in searching out ahovering position where interference to other unmanned aerial vehiclesis small through a random hill climbing algorithm.

The number of antennas of each unmanned aerial vehicle is two or more.

As is shown in FIG. 3, furthermore, the signal acquisition modulecomprises:

an acquisition module, wherein noise and out-of-band interferencesignals are filtered out through a band-pass filter for wireless signalsacquired by the unmanned aerial vehicles according to the operatingfrequency of the equipment, so that to-be-processed signals areobtained, and the channel state information of the physical layer isalso obtained.

Furthermore, the signal analysis module comprises:

a main path information extraction unit, wherein multi-path componentsarriving at a receiving antenna along different paths are separated bymeans of chromatic dispersion of a multi-path signal in the time domainand the power delay distribution characteristic, a power threshold valueis set, the path signal, greater than the power threshold, of the usersignal is regarded as main path information, and the main pathinformation is transformed from the time domain to the frequency domainthrough fast Fourier transform (FFT);

an angle of arrival calculation unit, wherein according to phasedeviation of the signal arriving at an antenna array, the timedifference of arrival of the signal at different antennas can be workedout, and the angle of arrival θ of the user signal along the direct pathis worked out through the MUSIC algorithm according to the differenttimes of arrival of the signal at the antenna array.

Furthermore, the signal processing module comprises:

a CSI processing unit, wherein the CSI processing unit is used forsmoothing acquired CSI data so as to eliminate signal coherence;

a beam forming unit, wherein based on the smoothed CSI data, a formingmatrix is calculated, the main lobe of the signal aims at the directionof arrival of the user signal, and the null aims at the direction ofarrival of interference signals, so that the radiant power of thesub-base stations is reduced, and interference to other users is alsoreduced.

Furthermore, the position searching module comprises:

a field distribution calculation unit, wherein for adjacent umnannedaerial vehicles, spatial distribution of wireless signals is estimatedaccording to known position information and a standard propagation modelof the wireless signals in the space;

a position searching unit, wherein through the random hill climbingalgorithm, each unmanned aerial vehicle searches out a position wherethe signal intensity of the adjacent unmanned aerial vehicle is weak andthen hovers at the position.

The unmanned aerial vehicles have the advantages of being flexible, lowin cost and the like. As the unmanned aerial vehicles are used as aerialsub-base stations, a service area can be well covered, the coverage areacan be controlled based on the mobility of the unmanned aerial vehicles,and thus interference to the adjacent cell is reduced. With thedevelopment of the MIMO technique, the interference management methodsuch as beam forming can be used through multiple antennas.

Based on the mobility of the unmanned aerial vehicle sub-base stations,interference between adjacent cells is reduced. According to theinvention, existing wireless network equipment is mainly used, noprofessional equipment is needed, and thus the mobile networking methodfor minimizing interference has extremely high universality.

The further detailed description of the invention is given with specificpreferred embodiments above, but the specific embodiments of theinvention are not limited to the description. Various simple deductionsor substitute made by those ordinarily skilled in the field withoutdeviating from the concept of the invention are all within theprotection scope of the invention.

1. A mobile networking method for minimizing interference, comprisingthe following steps: S1: unmanned aerial vehicles establish connectionand communication with ground base stations through a wireless relaymethod; S2: connection and communication between the unmanned aerialvehicles are established through a wireless self-networking method; 53:multiple unmanned aerial vehicles cooperate to form a cellular networkto provide wireless network services for users; S4: the unmanned aerialvehicles receive a received signal strength indicator fed back by userequipment and measure the angle of arrival of a signal beam from theuser equipment; S5: the unmanned aerial vehicles share the measurementinformation obtained in step S4, a cellular network signal for serviceusers of a specific unmanned aerial vehicle is regarded as a desiredsignal, cellular network signals of other unmanned aerial vehicles areregarded as interference signals, the main lobe of the desired signal ismade to aim at the direction of arrival of the service users and thenull is made to aim at the direction of arrival of the interferencesignals through a mobile interference alignment method and a beamforming method, and thus an optimal hovering position is searched out;S6: when the position of the user equipment changes, step S4 and step S5are repeated to search out the optimal hovering position again.
 2. Themobile networking method according to claim 1, wherein in step S1, theunmanned aerial vehicles establish connection and communication with theground base stations through the wireless relay method, and the linkfrequency is different from the communication frequency between thesub-base stations and users.
 3. The mobile networking method accordingto claim 1, wherein in step S3, multiple unmanned aerial vehiclescooperate, flight of the unmanned aerial vehicles is determined througha distributed control method, each unmanned aerial vehicle covers acertain area and provides wireless network services for users in thearea, and all the unmanned aerial vehicles form the mobile cellularnetwork.
 4. The mobile networking method according to claim 1, whereinstep S4 comprises: S41: the user equipment monitors the signalintensities of the unmanned aerial vehicles and feeds the informationback to the unmanned aerial vehicles; S42: the unmanned aerial vehiclesreceive signals from the service users, and the direction of arrival ofthe user equipment is estimated through the multiple signalclassification (MUSIC) algorithm.
 5. The mobile networking methodaccording to claim 1, wherein step S5 comprises: S51: the unmannedaerial vehicles share the information obtained in step S4 through theself network; S52: based on the mobile interference alignment method,each unmanned aerial vehicle searches out a position where interferencefrom the cellular network signals of other unmanned aerial vehicles isminimized through a random hill climbing algorithm; S53: the main lobeof the signal of each unmanned aerial vehicle is made to aim at thecorresponding service users through the beam forming technique, and thusinterference to other user equipment is reduced; S54: the optimalhovering position is searched out based on step S52 and step S53.
 6. Amobile networking system for minimizing interference, comprising: asignal acquisition module, wherein unmanned aerial vehicles are equippedwith multiple antennas and acquire signals from user equipment as wellas channel state information (CSI); a signal analysis module, whereinthe signal analysis module is used for determining the direction ofarrival of the user equipment through the multiple signal classification(MUSIC) algorithm; a signal processing module, wherein the signalprocessing module achieves beam forming through precoding according toknown signal state information; a position searching module, wherein theposition searching module is used for assisting each unmanned aerialvehicle in searching out a hovering position where interference to otherunmanned aerial vehicles is small through a random hill climbingalgorithm.
 7. The mobile networking system according to claim 6, whereinthe signal acquisition module comprises: an acquisition module, whereinnoise and out-of-band interference signals are filtered out through aband-pass filter for wireless signals acquired by the unmanned aerialvehicles according to an operating frequency of the equipment, so thatto-be-processed signals are obtained, and the channel state informationof a physical layer is also obtained.
 8. The mobile networking systemaccording to claim 6, wherein the signal analysis module comprises: amain path information extraction unit, wherein multi-path componentsarriving at a receiving antenna along different paths are separated bymeans of chromatic dispersion of a multi-path signal in the time domainand the power delay distribution characteristic, a power threshold valueis set, the path signal, greater than the power threshold, of the usersignal is regarded as main path information, and the main pathinformation is transformed from the time domain to the frequency domainthrough fast Fourier transform; an angle of arrival calculation unit,wherein according to phase deviation of the signal arriving at anantenna array, the time difference of arrival of the signal at differentantennas can be worked out, and the angle of arrival θ of the usersignal along the direct path is worked out through the MUSIC algorithmaccording to the different times of arrival of the signal at the antennaarray.
 9. The mobile networking system according to claim 6, wherein thesignal processing module comprises: a CSI processing unit, wherein theCSI processing unit is used for smoothing acquired CSI data so as toeliminate signal coherence; a beam forming unit, wherein based on thesmoothed CSI data, a forming matrix is calculated, the main lobe of thesignal aims at the direction of arrival of the user signal, and the nullaims at the direction of arrival of interference signals, so that theradiant power of the sub-base stations is reduced, and interference toother users is also reduced.
 10. The mobile networking system accordingto claim 6, wherein the position searching module comprises: a fielddistribution calculation unit; wherein for adjacent unmanned aerialvehicles, spatial distribution of wireless signals is estimatedaccording to known position information and a standard propagation modelof the wireless signals in the space; a position searching unit; whereinthrough the random hill climbing algorithm, each unmanned aerial vehiclesearches out a position where the signal intensity of the adjacentunmanned aerial vehicle is weak and then hovers at the position.